UC San Diego

Autism is characterized by marked dysfunction in social behaviors, but the neuropathology underlying these deficits is not fully understood. A potential biomarker of social dysfunction in autism is impaired brain activation and abnormal connectivity in regions involved in imitation, including the human mirror neuron system (hMNS). This dissertation uses multimodal neuroimaging techniques to further characterize the function of imitation-related brain areas in autism. FMRI is used to examine activation in hMNS areas during a task that required participants to observe and execute motor movements. Resting state functional connectivity MRI is used to examine correlations in spontaneous BOLD-signal fluctuations within an imitation network. Diffusion-weighted imaging is used to examine structural characteristics of white matter fiber tracts connecting key nodes of the same imitation network.

An additional goal of this dissertation is to investigate the effects of mu-rhythm-based neurofeedback training in individuals with autism. Currently, there are few therapeutic interventions that are effective in ameliorating the social symptoms of autism, and those that do exist require heavy investments of time, effort, and money. Neurofeedback training is a novel approach that has already been shown to be efficacious to some degree in this domain. Specifically, mu-rhythm based NFT, which targets a biomarker of hMNS function, may be able to induce lasting neuroplastic changes in the autistic brain and may in turn lead to positive behavioral outcomes. This dissertation is in part a study of the effects of 20 or more hours of NFT on task-related activation and functional connectivity in the hMNS in autism.